DE102012210376A1 - Method for determining artificial orthoimages of earth's surface, involves assigning predetermined pictorial material to amount of vegetation types suitable to respective vegetation type pictorial - Google Patents

Abstract

The method involves determining a node coordinate map grip (N) for a predetermined country surface. A vegetation type is determined from a predetermined amount of vegetation types dependent on a node attribute for a respective lattice node (K) of the node coordinate map grid for a predetermined vegetation layer. Pixel values for one or multiple portions of pixels of the orthoimages are determined dependently from the determined vegetation type. A predetermined pictorial material is assigned to an amount of vegetation types suitable to the respective vegetation type pictorial. An independent claim is also included for a device for determining artificial orthoimages.

Description

The invention relates to a method and a device for determining an artificial ortho-image.

An orthophoto is a distortion-free and true-to-scale mapping of the Earth's surface, derived from aerial or satellite images by photogrammetric techniques. Real orthophotos are increasingly used for map display in navigation devices. Here, navigation maps are supplemented with orthophotos for detailed presentation and orientation. This map display uses predominantly a superimposed representation in which an actual navigation map is superimposed on the orthophoto.

The object on which the invention is based is to provide a method and a device for determining an artificial ortho-image, which enables a simple and thus cost-effective provision of such an artificial ortho-image.

The object is solved by the features of the independent claims. Advantageous developments of the invention are characterized in the subclaims.

The invention is characterized by a method and a corresponding device for determining an artificial ortho-image with a predetermined number of pixels. Here, a node grid is determined for a given land area, wherein each grid node of the node grid network geographic coordinates and at least one node attribute are assigned, which is representative of a given climate and / or for a given climate zone and / or a predetermined eco zone and / or for a given Land use and / or for a given Hörtenbereich. For the respective grid node, a vegetation type from a predefined set of vegetation types is determined for at least one predefined vegetation layer as a function of the at least one node attribute. Furthermore, pixel values for at least a part of the pixels of the orthoimage are determined as a function of the determined vegetation types of the lattice nodes, wherein the vegetation types of the set are each assigned a predefined image material which is suitable for picturing the respective vegetation type.

The thus determined pixel values of the ortho-image can be signaled, in particular optically signaled by means of a suitably embodied display unit. Depending on the determined pixel values, further pixel values to be signaled can be determined. The ortho-image may represent a two-dimensional image or a three-dimensional scene. The image material may include a color and / or a two-dimensional texture and / or a spatial model, which characterizes an object and its material properties, light sources and the position and viewing direction of a viewer.

The predetermined climate zone may represent an ice climate and / or a tundra climate and / or a boreal climate and / or warm climate and / or subtropical climate and / or tropical climate. The predetermined climate can be a tropical rainforest climate and / or savanna climate and / or steppe climate and / or desert climate and / or Etesienklima and / or humid climate and / or Sinian climate and / or wet continental climate and / or trans-Siberian climate and / or summer-cold climate and / or or Tundrenklima and / or ice climate. The eco zone may represent a polar and subpolar zone and / or boreal zone and / or wet center widths and / or dry center widths and / or mediterranean ecozone and / or laurel ecozone, and / or dry tropics and / or intermittent tropics and / or humid tropics ,

The predetermined land area is preferably a given land area of the earth's surface characterized by its topography. The topography represents the natural surface of the earth with its heights, depths, irregularities and shapes. Topography in the sense of cartography, in addition to the terrain, also includes the surface objects firmly connected to the terrain. Each grid node represents a given section of the given land area.

The amount of vegetation types may include both different plant species as well as different ground and / or soil conditions, for example sand, a tar surface, rocks, gravel, soil and water as well as various object textures such as roof tiles, walls and wood elements.

A determination of the artificial Ortho image can advantageously be done with low computing capacity and thus be done very quickly. The determination of the artificial ortho-image can thus take place during a running time, for example during a current operating phase of a navigation device, and thus in conjunction with a current map display of the navigation device.

The determination of the artificial ortho-image during a runtime further enables a memory requirement to be kept low. Storing real orthophotos that can be read out of memory as needed takes up a lot of storage space compared to the data that must be provided for the determination of the artificial ortho-image.

Advantageously, the artificial ortho-image can be very easily linked to a digital map, for example a road map, since the digital map can use a database based on nodes to which geographic coordinates are assigned. A correct, consistent overlay of the digital map and the artificial Ortho image is therefore very easy.

Advantageously, a resolution of the artificial Ortho image can be adjusted as needed. Here, resolution is the ability of an image to be able to reproduce certain smallest structures. For digital images, the amount of pixels per unit area provides an orientation for the resolution. In real orthophotos, the resolution is limited by the optical resolution of a recording device that has captured the orthophoto.

The artificial ortho-image also has the advantage that no disturbing influences, such as clouds and / or shadows, are present in the image. Advantageously, however, further elements can be added as needed to the ortho-image, so that a realistic representation is possible.

Capturing real orthophotos is very expensive. Providing real orthophotos for a navigation system of a vehicle can therefore be very expensive. The respective real orthophoto is static. This means that if a time-dependent or season-dependent presentation is to be made for a particular area, for example in Germany, several real orthophotos for one and the same area must be recorded and provided. The artificial ortho-image has the advantage that it can be adapted flexibly to current boundary conditions, for example to a daytime-dependent solar irradiation and / or a season-dependent vegetation in a respective area. Advantageously, the respective artificial ortho-image can be dynamically updated and / or adapted to user interests and / or to a current situation in the environment of the represented area. Here, both temporary influences and permanent influences can be taken into account.

Further, the ortho images obtained for various predetermined land areas can be determined for the respective land areas such that the respective ortho images have a uniform appearance. Furthermore, the appearance can be easily and flexibly changed and / or adapted.

The required data for determining the vegetation type can be stored in predetermined databases and retrieved from there as needed. In particular, data can be used that are already made available to a large number of users, for the most part free of charge.

The artificial ortho-image can be used for object recognition. For example, areas can be identified where snow is expected to be located in these areas. Depending on this information, a route for bypassing this area can be determined by means of a suitably designed navigation device. The navigation device can determine, for example, a route that uses a toll tunnel instead of a route over a mountain pass.

In an advantageous embodiment, the grid nodes are determined such that the respective grid node represents a center of a Voronoi region. Advantageously, this allows a very simple determination of a suitable node grid for the given land area. The node grid thus represents a Voronoi diagram for the given land area.

In a further advantageous embodiment, an impact probability for at least one vegetation type of the set is determined for the respective grid node depending on the at least one node attribute of the respective grid node. Furthermore, the vegetation type of the grid node of the at least one vegetation layer is determined as a function of the probabilities of the at least one vegetation type determined for the grid node. This can advantageously contribute to the fact that the type of vegetation can be determined very reliably and thus an artificial ortho-image that maps the reality very well.

In a further advantageous embodiment, for the respective grid node for at least one predetermined image synthesis layer, a display element is determined from a predefined set of presentation elements, depending on the at least one node attribute and / or a predetermined presentation size. The pixel values are determined for the at least one part of the pixels of the ortho image as a function of the determined presentation element, wherein the presentation elements of the set each represent a predetermined further image material. Advantageously, this can make a contribution that the artificial ortho-image depicts actual conditions very realistically. Additional image processing layers can be introduced and thus additional information added. The introduction of further image processing layers allows, for example Shading to take into account and / or a snow cover. The representation variable may include, for example, a time of day and / or a season and / or a predetermined viewing perspective and / or a light color and / or a light intensity and / or a light irradiation direction.

In a further advantageous embodiment, depending on at least one predetermined first rule, exchange nodes are determined in the node grid and in each case at least one of the node attributes of the respectively determined exchange node is replaced by at least one predetermined exchange node attribute. Advantageously, this makes it possible to provide replacement data for areas for which no data and / or incorrect data are available with regard to the climate and / or the climatic zone and / or the ecozone and / or the land use and / or the altitude range, so that these areas in the artificial ortho-image can be at least approximately imaged. Furthermore, this makes it possible to change a land use for areas such that a natural image impression is created for a viewer of the ortho-image. Here, a selection of the area whose land use is changed can be selected at random. The change may include both a different type of land use, including a more detailed description of land use. This makes it possible, for example, to change an area with a larger forest area in such a way that the area also has forest clearings.

In a further advantageous embodiment, depending on at least one predetermined second rule, the replacement nodes in the node grid are determined and the determined vegetation type or the determined display element is replaced by a predetermined further vegetation type or by a predetermined further presentation element. This has the advantage that the replacement data can be made very easy.

In a further advantageous embodiment, predetermined grid points are assigned to each grid node and, depending on at least one predetermined third rule, the replacement nodes are determined in the node grid and the determined pixel values for the pixels of the grid node are replaced by further predetermined exchange pixel values. This has the advantage that the exchange nodes can be determined very easily and the replacement data can be made very easily available.

Embodiments of the invention are explained below with reference to the schematic drawings.

Show it:

1 an embodiment of an extended navigation system,

2 an exemplary initial arrangement of a node grid,

3 an embodiment of a vegetation model,

4 an exemplary conversion of the vegetation model into an image synthesis model,

5 an exemplary arrangement of presentation elements in one of the image synthesis layers and

6a to 6c an example of determining exchange nodes.

Elements of the same construction or function are provided across the figures with the same reference numerals.

1 shows an embodiment of an extended navigation system 10 , The advanced navigation system 10 For example, it can be arranged in a vehicle and designed as a vehicle navigation system. Alternatively or additionally, it is also possible that the advanced navigation system 10 is designed as a mobile passenger navigation system. The advanced navigation system 10 includes, for example, a navigation unit 20 with a position determination unit 30 , a route determination unit 40 and a central control unit 50 ,

Furthermore, the extended navigation system includes 10 For example, a control unit 70 , an output unit 80 , a database 90 , a communication interface 95 and a device 100 for determining an ortho-image.

The position determination unit 30 the navigation unit 20 For example, it is designed to determine a current position of the vehicle. The position determination unit 30 may include a Global Positioning System (GPS) receiver and / or position detection sensor devices. The route determination unit 40 may be formed, depending on a current position of the vehicle and / or a predetermined starting location and a predetermined destination, to determine a route depending on predetermined map data.

The central control unit 50 can be formed, predetermined programs of the navigation unit 20 perform. The position determination unit 30 , the route determination unit 40 and the central control unit 50 are about one, for example bus 60 the navigation unit 20 signal-technically coupled.

The navigation unit 20 For this purpose, for example, it is signal-wise coupled with the database 90 , Database 90 For example, it is designed to store the map data.

Further, the navigation unit 20 signal-technically coupled with the operating unit 70 , By means of the control unit 70 can be a user of the navigation system 10 for example, certain functions of the navigation unit 20 select and thus for execution by the navigation unit 20 bring.

The navigation unit 20 is for example signal-coupled with the output unit 80 , The output unit 80 For example, it can comprise an optical and / or acoustic and / or haptic output device, for example a display and / or a loudspeaker.

The navigation unit 20 is for example signal-coupled with the communication interface 95 which has, for example, an air interface. This allows the navigation unit 20 For example, receive data from an external database.

The device 100 for determining the ortho image can be signal-technically coupled to the control unit 70 , In particular, the device can 100 with the operating unit 70 be signal-technically coupled such that depends on predetermined operating operations of the operating unit 70 For example, an appearance of the artificial ortho-image and / or a size and / or an area for the artificial ortho-image can be predetermined by the user.

The device 100 is for example signal-coupled with the output unit 80 , The device 100 may be formed, the output unit 80 to control such that the determined ortho-image by means of the output unit 80 , in particular by means of the optical output device, is signaled.

The device 100 is for example signal-coupled with the communication interface 95 , This allows the device 100 for example, download data from predetermined external databases.

Furthermore, the device 100 be technically coupled with the database 90 and thus be trained on those in the database 90 to access stored map data.

The device 100 is designed to determine an artificial ortho-image with a predetermined number of pixels. In this case, a node grid N is determined for a given land area, wherein each grid node K of the node grid network N geographic coordinates are assigned and at least one node attribute that is representative of a given climate and / or for a given climate zone and / or a predetermined eco zone and / or for a given land use and / or for a given altitude range.

2 shows an example of such a node grid N. 2 shows an initial arrangement comprising, for example, a regular triangular grid. Alternatively, it is possible that the node grid comprises a pixel grid. The grid may have any shape. Each grid node K represents a given section of the given land area. The respective grid node K can be assigned a wide variety of information that can be read, for example, from various predetermined databases. The databases may include external databases, in particular off-board databases, as well as the database 90 of the navigation system 10 , The respective grid node K may additionally or alternatively be assigned further node attributes which are representative, for example, of a surface orientation and / or a ground cover and / or a slope of the terrain and / or of variables which characterize dynamic influences. One of the grid nodes K can be assigned, for example, the specific node attributes forest, in altitude 1500 and in climate zone Tundra.

The device 100 For example, it may also be designed to determine the grating nodes K in such a way that the respective grating node K represents a center of a Voronoi region.

The device 100 Furthermore, it is configured to determine a vegetation type from a predefined set of vegetation types for the respective grid node K for at least one predefined vegetation layer, depending on the at least one node attribute. In particular, the device can 100 be formed to determine a vegetation model for the respective grid node K.

3 exemplifies such a vegetation model. The vegetation model includes a predetermined number of vegetation layers. For example, the vegetation model may include a first vegetation layer L1 that is representative of a soil layer. Alternatively or additionally, the vegetation model may comprise a second vegetation layer L2, which is representative of a herb and / or shrub layer. Alternatively or additionally, the vegetation model may include a third vegetation layer L4 that is representative of a tree layer.

The vegetation type for the respective grid node K can be determined, for example, for at least one of the vegetation layers of the vegetation model depending on a height and / or a height range, a gradient, a land use and / or a climate, which are assigned to the respective grid node K.

For example, the vegetation model uses a semantic description for the characterization of the respective grid node K. Preferably, the vegetation model comprises at least the first vegetation layer, which represents the soil layer. For example, the vegetation types of the second vegetation layer may also depend on the first vegetation layer.

The device 100 For example, it may be configured to determine for the respective grid node K an encounter probability for at least one vegetation type of the set depending on the at least one node attribute of the respective grid node K as well as the vegetation type of the grid node K of the at least one vegetation layer depending on the grid node K determined Hit probability of the at least one type of vegetation.

For example, for the grid node K, a respective characteristic value for the vegetation types of the at least one vegetation layer can be determined. The characteristic value is, for example, representative of an impact probability of the respective vegetation type in the given section of the land area which the grid node K represents. For example, for a first vegetation type representing, for example, a beech tree, the key figure value may be determined depending on a probability of occurrence of a beech tree at a certain altitude and / or in a particular climatic zone and / or terrain with a given grade and / or or at a certain land cover. Furthermore, the characteristic value for a second vegetation type, which represents a spruce tree, for the same grid node K can be determined. The type of vegetation which has the larger characteristic value can, for example, be selected as the vegetation type for the at least one vegetation layer of the lattice node K.

The device 100 is configured to determine pixel values for at least a part of the pixels of the ortho image depending on the determined vegetation types of the grid nodes K, wherein the vegetation types of the set are each assigned a predetermined image material that is suitable to image the respective vegetation type.

For this purpose, the vegetation model, for example, first implemented and / or expanded to a picture synthesis model. For this purpose, the device 100 be formed to determine a picture synthesis model. The image synthesis model can also be called a rendering model. 4 shows an example of a conversion of the vegetation model in the image synthesis model. The image synthesis model can comprise, for example: a first image synthesis layer S1, which represents, for example, borders, and / or a second image synthesis layer S2, which is representative of a transformed soil layer, and / or a third image synthesis layer S3, which is representative of a transformed herb and / or or shrub layer, and / or a fourth image synthesis layer S4 representative of a shadow layer and / or a fifth image synthesis layer S5 representative of a transformed tree layer and / or a sixth image synthesis layer S6 representative of a snow layer.

The respective vegetation layer of the vegetation model can be assigned to one or more image synthesis layers. Preferably, the number of image synthesis layers of the image synthesis model is greater than the number of vegetation layers of the vegetation model. The device 100 Therefore, it may be configured to determine a display element D from a predefined set of display elements for the respective grid node K for at least one predefined image synthesis layer, depending on the at least one node attribute and / or a predefined display variable. The device 100 In this context, it may be configured to determine the pixel values for the at least one part of the pixels of the ortho image as a function of the determined display element D for the at least one predefined image synthesis layer, wherein the display elements of the set each represent a predefined further image material. The introduction of further layers makes it possible to take into account shading and / or snow cover and / or cloud cover. The representation variable may include, for example, a time of day and / or a season and / or a predetermined viewing perspective and / or a light color and / or a light intensity and / or a light irradiation direction.

Furthermore, the device 100 be formed to transform the vegetation types determined for the respective vegetation layer into corresponding display elements D for the image synthesis layer corresponding to the vegetation layer. The transformation can be done here For example, an implementation of the semantic characterization of the vegetation type in a graphical, in particular computer graphics, representation of the vegetation type include. Thus, for example, the display element D of the third image synthesis layer S3 of one of the grid nodes K can represent, for example, the image material associated with this grid node K for the first vegetation layer L1. The image material, for example, may include a colored texture (in the sense of computer graphics), a size and an orientation or a twist. The display element D of the fourth image synthesis layer S4 of one of the grid nodes K represents, for example, another image material that is suitable for generating shadow effects.

Both the vegetation model and the image synthesis model can be specified differently for each grid node K. In particular, the vegetation model and / or the image synthesis model for grid nodes K assigned to different geographical regions can be specified differently.

The image synthesis can be done in real time. For this purpose, the device 100 For example, have two parallel processing units.

5 shows an exemplary arrangement of display elements D of one of the image synthesis layers. The respective display element D, which is assigned to one of the grating nodes K, can in this case represent a predetermined section of the ortho image. The respective section may, for example, comprise a square of a predetermined size. The presentation elements D of the respective image synthesis layer can be arranged overlapping. Alignment and arrangement of the display elements D in the respective image synthesis layer can be uniform or different.

Depending on the respective presentation elements D of the respective image synthesis layers of the grid node K, a resulting representation element for the respective grid node K is determined. This can be done, for example, depending on a rendering algorithm.

Furthermore, it can be provided that the device 100 is formed, depending on at least one predetermined first rule exchange nodes in the node grid N to determine and replace at least one of the node attributes of each determined exchange node by at least one predetermined exchange node attribute.

The 6a to 6c illustrate such an exchange. For example, it may be provided that a node search pattern KS (see 6b ) is given with a predetermined number of nodes and with one or more predetermined node attributes. This node search pattern KS is compared with predetermined grid network sections of an output node grid (see 6a ). Depending on a comparison result of the node search pattern KS with the respective grid section, the grid network exit is replaced by a node replacement pattern KE (see 6c ). Alternatively or additionally, it may be provided that the device 100 is formed, depending on at least one predetermined second rule to determine the exchange nodes in the node grid N and to replace the determined vegetation type or the determined display element D by a predetermined additional vegetation type or by a predetermined additional display element.

Alternatively or additionally, provision may be made for each grid node K to be assigned predetermined pixels and the device 100 is formed, depending on at least one predetermined third rule to determine the exchange nodes in the node grid N and to replace the determined pixel values for the pixels of the grid node K by further predetermined exchange pixel values.

For example, relations between the grid nodes K can be modeled by the given rules. For example, the input data can be changed and, for example, a path between two fields can be modeled. The rules can be set in such a way that inconsistencies can be avoided, for example that a lake never lies on a steep slope.

LIST OF REFERENCE NUMBERS

10

extended navigation system

20

navigation unit

30

Position determining unit

40

Route determination unit

50

central control unit

60

bus

70

operating unit

80

output unit

90

Database

95

Communication Interface

100

Device for determining an ortho-image

D

presentation element

K

grid nodes

KE

Node substitution patterns

KS

Node search patterns

L1

first vegetation layer

L2

second layer of vegetation

L3

third vegetation layer

N

Node grid

S1

first image synthesis layer

S2

second image synthesis layer

S3

third image synthesis layer

S4

fourth image synthesis layer

S5

fifth image synthesis layer

S6

sixth image synthesis layer

Claims (8)

Method for determining an artificial ortho-image having a predetermined number of pixels, in which A node grid (N) is determined for a given land area, wherein each grid node (K) of the node grid (N) is associated with geographical coordinates and at least one node attribute that is representative of a given climate and / or climate zone and / or a predetermined eco-zone and / or for a given land use and / or for a given altitude range, - For the respective grid node (K) for at least one predetermined vegetation layer, a vegetation type from a predetermined amount of vegetation types is determined depending on the at least one node attribute, and Depending on the determined vegetation types, the grid nodes (K) are assigned pixel values for at least a part of the pixels, wherein the vegetation types of the set are each assigned a predefined image material which is suitable for picturing the respective vegetation type. The method of claim 1, wherein the grid nodes (K) are determined such that the respective grid node (K) represents a center of a Voronoi region. Method according to claim 1 or 2, in which - For the respective grid node (K) an Antreffwahrscheinlichkeit for at least one vegetation types of the set is determined depending on the at least one node attribute of the respective grid node (K) and - The vegetation type of the grid node (K) of the at least one vegetation layer is determined depending on the determined for the grid node (K) Antreffwahrscheinlichkeit the at least one vegetation types. Method according to one of the preceding claims, in which - For each grating node (K) for at least one predetermined image synthesis layer, a display element (D) is determined from a predetermined set of display elements depends on the at least one node attribute and / or a predetermined representation size and - The pixel values for the at least a part of the pixels of the ortho image are determined depending on the determined display element (D), wherein the display elements of the set each represent a predetermined additional image material. Method according to one of the preceding claims, in which exchange nodes in the node grid network (N) are determined as a function of at least one predetermined first rule and in each case at least one of the node attributes of the respectively determined exchange node is replaced by at least one predetermined exchange node attribute. Method according to one of the preceding claims, in which, depending on at least one predetermined second rule, the replacement nodes in the node grid (N) are determined and the determined vegetation type or the determined display element (D) is replaced by a predetermined further vegetation type or by a predetermined further presentation element , Method according to one of the preceding claims, in which each grid node (K) is assigned predetermined pixels and, depending on at least one predetermined third rule, the exchange nodes in the node grid (N) are determined and the determined pixel values for the pixels of the grid node (K) by further predetermined exchange pixel values are replaced. Contraption ( 100 ) for determining an artificial ortho-image, which is adapted to carry out a method according to claims 1 to 7.

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